Tanya Gupta

🚀 Sit back, relax, and dive into this must-read case study! 🎓 Whether you're a student, an MBA candidate, or a Product Manager, this in-depth breakdown is for EVERYONE looking to up their game. 🔍 This case study offers valuable insights into problem-solving, strategic thinking, and practical execution. Whether you're prepping for your next big career move or just want to expand your knowledge, this will guide you through real-world scenarios. ✨ Why read it? Learn how to approach complex challenges Understand key frameworks and strategies Gain insights that can boost your career 💼 If you're serious about growing in Product Management or want to ace your next business challenge, this case study is your go-to resource! 👉My all case study are available on Topmate please check in comment Not expensive like Cold play ticket😂 #ProductManagement #CaseStudy #CareerGrowth #BusinessInsights #MBA #Learning

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#Google Interview: Learning from the Experience (Associate Product Manager) Had my #Google interview for an #Associate Product Manager role, and while I didn't land the offer this time, it was an incredible learning experience! The prompt focused on a product similar to Zoom or Teams, and I wanted to delve deeper than just typical features. Here's what I explored: 1. User Personas: I segmented users into tech-savvy and non-tech-savvy groups to ensure a seamless experience for all. 2. Beyond the A/V: I emphasized the importance of replicating the "in-person" feel for effective communication. Current platforms excel in audio and visuals, but lack the environmental context (aroma, physical touch) that facilitates richer conversations. 3. Learning From Deviation: I explored the potential of VR/AR, which, while interesting, wasn't what the question aimed for. This highlighted the importance of critical thinking and staying focused on the prompt. 4. Managing Unexpected Circumstances: The interview had a delay and then went beyond an hour, which caused some initial panic and impacted my focus. It was a valuable lesson in maintaining composure and adapting under pressure. Looking #Forward: Thank you to the Google team for this insightful interview. I'm committed to honing my critical thinking skills and staying agile during interviews. This experience fuels my passion for product management, and I'm excited for the next opportunity! #GoogleInterview #ProductManagement #LearningExperience #GrowthMindset Feel free to add in the comments: #Specific examples of features you proposed for different user personas regarding the "in-person" feel. #How you'll manage unexpected circumstances in future interviews. By being transparent about your thought process and learnings, you can: #Connect with other job seekers who might have had similar experiences. #Showcase your critical thinking and adaptability to potential employers. #Demonstrate a growth mindset which is highly valued in tech companies.

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Hello!! I found this video really helpful by Sandeep Rani Pradeep Kumar with the strategies that he has mentioned in this video on the techniques to optimize the job application process. Hope this helps.

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Google is offering Data Analytics courese for everyone. Repost so that all can take benifits Big companies value your SKILLS! Become a Google Certified Data Analytics within a few months. 👉 https://lnkd.in/g9fH3pw2 1. Google Data Analytics: In this program, you’ll learn in-demand skills that will have you job-ready in less than 6 months. No degree or experience required. 🔗 https://lnkd.in/gWudVANX 2. Learn Python Basics for Data Analysis Learn how to use and write functions, practice with data analysis, and work on your first algorithm! 🔗 https://lnkd.in/gZRCUjmU 3. Data Analysis with R Programming In this course, you’ll learn about the programming language known as R. You’ll find out how to use RStudio, the environment that allows you to work with R. 🔗 https://lnkd.in/gnrqM-iu 4. Foundations: Data, Data, Everywhere This course will help you gain an understanding of the practices and processes used by data analysts in their day-to-day job. 🔗 https://lnkd.in/gtZ2Mnhx 5. Ask Questions to Make Data-Driven Decisions This course will help you learn how to ask effective questions to make data-driven decisions while connecting with stakeholders’ needs. 🔗 https://lnkd.in/geUnkPts 6. Process Data from Dirty to Clean This course will help you learn how to check and clean your data using spreadsheets and SQL as well as how to verify and report your data cleaning results. 🔗 https://lnkd.in/g3pmcR-u 7. Share Data Through the Art of Visualization In this course, you’ll learn how to visualize and present your data findings as you complete the data analysis process. 🔗 https://lnkd.in/gZhf8pPD 8. Analyze Data to Answer Questions In this course, you’ll learn how to organize and format your data using spreadsheets and SQL to help you look at and think about your data in different ways. 🔗 https://lnkd.in/gpV2wJd9 9. Get Started with Python 🔗 https://lnkd.in/gcDGVZhf 10. Go Beyond the Numbers: Translate Data into Insights 🔗 https://lnkd.in/grnGTJmq 11. The Power of Statistics 🔗 https://lnkd.in/gr5mUwgr 12. Regression Analysis: Simplify Complex Data Relationships 🔗 https://lnkd.in/giJrEveW 13. The Nuts and Bolts of Machine Learning 🔗 https://lnkd.in/greJF9pg 14. Google Advanced Data Analytics Capstone 🔗 https://lnkd.in/g97AjH47 Follow Dr.Vaishali Dixit for more contents..🤗 PDF Credit: Chartio (Recommended) #DataAnalytics #DataScience #dataanalysis LinkedIn Learning LinkedIn for Creators

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I have four table given below and write query to get the expectd output--- Student Student_ID Student_Name Class 1 aaa 1 2 bbb 2 Teacher TID Teacher_Name 1 hhh 2 ggg Student_Subject STUID SUBID Teacher_ID 1 1 1 2 1 1 Student_Marks Student_ID SUBID Marks Class 1 1 50 1 1 2 90 1 2 1 50 1 2 2 90 1 Q.1 Write a query to find 2nd highest marks of a student SELECT Student_ID, Marks FROM (   SELECT      Student_ID,      Marks,      DENSE_RANK() OVER (PARTITION BY Student_ID ORDER BY Marks DESC) AS rank   FROM Student_Marks ) ranked_marks WHERE rank = 2; Q. 2 Write a query To find the teachers who are not teaching any subjects SELECT t.TID, t.Teacher_Name FROM Teacher t LEFT JOIN Student_Subject ss ON t.TID = ss.Teacher_ID WHERE ss.Teacher_ID IS NULL; #interview #quesforADE #SQL

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Unveiling Corona Trends: Average Confirmed, Deaths & Recovered Cases (SQL) During my internship at Mentorness, I delved into corona data analysis using SQL to uncover crucial trends! Here's a glimpse: 1. Average Case Explorer: I calculated the average number of confirmed cases, deaths, and recovered cases. 2. Unveiling the Landscape: By sorting these averages in ascending order, I identified which category (confirmed, deaths, recovered) typically had the highest average. 3. Data-Driven Insights: This analysis provided valuable insights into the overall spread and recovery patterns of the virus. Curious to see the SQL code behind the scenes? Feel free to connect and discuss my data analysis approach!

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I got Chicago crime data from their portal that has 8.07M rows and 22 columns from 2001 till date (May 31st, 2024). January - May 31st, 2024 has 94.9k data points. Also, I have Chicago Public Schools Reports Cards data. Though it is not up to date. It has 566 rows and 79 columns. My weekend has been made already. I am going to, Clean the data. Prepare the data. Analyze the data. Visualize the data. Build dashboards. I am going to export the Chicago and public data to Tableau after cleaning the data. Build a predictive algorithm. Write documentation about the project that will be published on my medium blog. Publish the Python code for the project on my GitHub. The dashboards on my Tableau profile. Tools for the project: Python and Tableau. I can’t wait to handle and explore this data. I am excited about the insights that will derived from the data even though I haven’t started the show yet. As I said, my weekend has been made already and I can’t wait to jump in immediately. Data Detective in the building.

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Want to learn Tableau & transition into analytics? I’ll be starting a new cohort next month mid/end (only on weekends) Enroll here for early notification: https://lnkd.in/gNrEc7i6 P.S: Below is the feedback from student of the last cohort

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Looking for data analytics job on LinkedIn ???? But don't know how to start?? here i am sharing my experience, 👇 LinkedIn is your ultimate toolkit for finding the perfect job match! Here's a step-by-step guide to help you navigate the process: 1. Optimize Your Profile: Start by crafting a compelling LinkedIn profile that highlights your skills, experience, and passion for data analytics. Use keywords relevant to the field to increase your visibility to recruiters. 2. Network, Network, Network: Expand your professional network by connecting with peers, industry experts, and recruiters in the data analytics field. Engage in meaningful conversations, join relevant groups, and attend virtual events to build relationships. 3. Follow Relevant Companies: Stay updated on job openings by following companies that align with your career aspirations. Turn on job alerts to receive notifications when new data analyst positions are posted. 4. Use LinkedIn Job Search Tools: Explore the Jobs tab and use filters to narrow down your search based on location, industry, experience level, and more. Save your favorite job listings and set up job alerts to stay informed about new opportunities. 5. Customize Your Application: Tailor your resume and cover letter to each job application, highlighting your relevant skills and experiences. Personalize your message when reaching out to recruiters or hiring managers to express your interest in the position. 6. Showcase Your Skills: Leverage LinkedIn's multimedia features to showcase your data analysis projects, case studies, and certifications. A strong portfolio can set you apart from other candidates and demonstrate your expertise in action. 7. Prepare for Interviews: Research the company and role thoroughly, and be ready to discuss your past experiences and problem-solving abilities. Practice common data analyst interview questions and be prepared to demonstrate your analytical skills. 8. Stay Persistent and Positive: Finding the right data analyst job may take time, so stay persistent and maintain a positive mindset throughout your job search journey. Every rejection is a step closer to your dream job! Remember, LinkedIn is more than just a job search platform,it's a community of professionals eager to support you in your career growth. So dive in, connect with like-minded individuals, and let's embark on this exciting journey together! 🚀💼 Follow Picnic Rautaray for more valuable contents. #DataAnalytics #careeradvice #LinkedInTips #jobsearch #professionaldevelopment #dataanalyticsjob #linkedinjobsearch #jobsearchtips

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Are you preparing for your next Data Science or Data Analyst interview? One of the key skills every recruiter is looking for is Advanced SQL proficiency. Understanding complex queries, optimizing performance, and managing large datasets are crucial for success. Here are a few must-know advanced SQL questions that could give you an edge: 1. What is a CTE (Common Table Expression)? Ans. CTEs make queries more readable and easier to manage. They help in simplifying recursive queries, and they are often used in complex joins. 2. How do you handle performance tuning in SQL? Ans. Techniques like indexing, query optimization, and understanding execution plans can significantly speed up database queries. 3. What is a window function? How is it different from GROUP BY? Ans. Window functions are used to perform calculations across a set of table rows related to the current row, without collapsing rows as in GROUP BY. 4. Explain the difference between DELETE, TRUNCATE, and DROP. Ans. Each serves a distinct purpose in data removal. DELETE allows for conditions, TRUNCATE is faster and removes all rows, while DROP deletes the table structure. 💡 Pro Tip: Before your interview, practice writing queries that optimize data retrieval from large tables. Understanding database design is just as important as mastering the syntax. 👉 Follow me for more tips on SQL and data science interviews, and feel free to drop your own SQL interview questions in the comments below! 💬 #SQL #DataScience #DataAnalytics #SQLInterviewQuestions #AdvancedSQL #CareerTips #InterviewPrep #DatabaseManagement #TechInterview

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Exciting News!!! Meta just launched a Data Analytics Certification on Coursera   Many people have reached out to me about the Meta Marketing Analytics Course on Coursera    This is amazing news for folks who have taken the Meta Marketing Analytics Course as some of the modules are maintained such as Introduction to Data Analytics, Data Analytics with Spreadsheet and SQL, Python Data Analytics, and Statistics for Marketing    There is one additional course that is not live until June 20th, 2024. This course is called Introduction to Data Management    I did a review of the introductory part of the first 4 parts of the certificated course and many found it valuable    This course is an 82-hour or 5.5-week course that covers SQL, Python, Excel, and Tableau (assuming you spend approx. 15 hours per week studying).    I like the fact that week 1 introduces the learner to KPIs and a framework for data analytics called OSEMN (Obtain, Scrub, Explore, Model, and Interpret)    The instructors for this course Victor Geislinger, @Brandon Larkin, and Anke Audenaert did a great job at explaining some of the concepts in SQL, Python, Google Sheets, and Tableau.     As a beginner, this will give you a head start on how to use these tools that are widely used for data analytics From a Usability standpoint. Which measures how valuable is the course in helping learners get a job.    I give a 5 star on Usability as this particular course helped me get a Job as a Marketing Analyst for a Marketing Agency     Though I did not accept the offer, I learned a lot from the experience hence my 5-star review on Usability    The course has a capstone project in the last week whereby you are given instructions on how to build a case study using the OSEMN framework    See a link to my GitHub portfolio of the project I built that helped me get a job with a good salary for a Marketing Agency    Some courses are good to take and others are life-changing. Though this course is only an introductory course, it is one of those life-changing courses    If you are interested in getting started in a career in Data Analytics, I highly recommend this course    #dataanalytics #dataanalyts #learninganddevelopment 

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Many working professionals struggle to revise tools like SQL. 😥 And, frankly, that was the case with me too. As with a full time job picking up self-learning becomes hard. However, one thing that helped me greatly was preparing through CheatSheet. Take the help of this sheet and understand the topics to be covered in SQL Basics:  🚩 SQL Data types 🚩 Functions & View 🚩 Indexes 🚩 Stored Procedures 🚩 Using SQL Constraints 🚩 Trigger  🚩 SQL Query 🚩 SQL Function Now, if you want to master these topics effectively, make sure you have the right mentor & support. I’d suggest Bosscoder Academy. Check them here: https://bit.ly/4dnD8DL They can help you with: ✅ Structured curriculum to learn SQL, Data Visualization, and Machine Learning. ✅ Getting you job-ready for top companies. ✅ Personal mentorship from experienced Data professionals. ✅ Live classes, project-based learning, and access to a talented community of people with similar goals of upskilling. #sql #dataanalyst #linkedin #data

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Today was my day 23 of looking for a data analyst job and this is my first interview experience As you might know, yesterday I shared about the FIRST interview of my life + data analyst role I was 100% PREPARED from my side From my resume to their JD From their company's history to my portfolio projects I was well-versed Just after the greetings The interviewer said "I don't care what projects you have made" "I want to know in which data analysis you are the most proficient" I said, I know how to perform data analysis in all the 4 major tools But my proficiency level of tools is like this Excel -> SQL -> Power BI -> Python "Okay, so you are MORE proficient in Excel....." I think this was the moment where I STABBED myself I knew the company is based MORE on Excel and then SQL I prepared all the Excel and SQL topics from YouTube and ChatGPT EVERYTHING from basic to advanced formulas that are taught on every Data Analyst YT channel I expected that the interviewer would ask me a question and I would answer it with a function/formula And I will share how that specific thing works BUT all the questions were scenario-based and on Advanced Excel The questions he asked, I was NEVER aware of such topics Even though, I have spent so much time in Excel There was a question like: "How can you create a VLOOKUP formula by just using only the Filters?" There were so many questions on filter formula I was a little bit aware of it but NEVER used it in any of my works Another question was like, I have 4 tables in different sub-sheets and all are uneven. I want to connect them Every question was based on a scenario And I realized this after some hours of interview competition I thought, the answer would be only a function/formula But that was NEVER the case When he was explaining the solution, there was a whole PROCEDURE in every answer So that was not possible by only using a formula/function only Right after the first question, I started answering He STOPPED me and gave me a tip In technical interviews, you should NEVER answer directly after the question Take a pause. Think for a moment Structure your whole answer. Use pen and paper I must say, the interviewer was very kind-hearted and calm person He KNEW this is my first interview He gave me so many tips that would definitely help me in my FUTURE interviews Later he told me, it might be possible I only asked you the questions on that topic only of which you are not aware This doesn't show that you don't know Excel Also, I don't LIKE to share my silly mistakes here OPENLY But I DO it, so you do not make such mistakes in YOUR interviews These were just a FEW glimpses where I was at the DOWN point Some GREAT things also happened yesterday LinkedIn is limiting me to extend this post I will continue the remaining tomorrow ----- 💜 I am Ayan Khan, I share my everyday journey as a Data Analyst 🚀 Follow me because I post my daily INSIGHTFUL job experiences

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Tiger Analytics Data Analyst Interview Experience (1-3 Years Experience) 👇 1. Tell me about your background and current role. 2. Rate your SQL proficiency from 1 to 10 and justify your rating. 3. Write an SQL query to find the highest-paid employee in each department who joined in the last 3 years. 4. Explain window functions in SQL and provide an example of ranking products by quarterly revenue. 5. How would you merge two DataFrames in Python and calculate the average order value for each customer? 6. Write a Python code snippet to calculate cumulative revenue using Pandas. 7. Describe a project where you used Power BI for data visualization. 8. What challenges have you faced while working with large datasets, and how did you solve them? 9. How would you resample a time series dataset to get monthly totals in Python? 10. Discuss a time when you faced difficulties during a project and how you overcame them. 11. How do you handle missing data in a dataset, and what methods do you use for imputation? 12. Explain how you would optimize a slow SQL query. 13. Describe your experience with data cleaning and the steps you follow. 14. How would you validate the accuracy of a data model or report? 15. What key metrics would you track when analyzing the performance of a business using data? Now, if you’re looking for a platform to help you with your end-to-end interview preparation, you can check out the programs by Bosscoder Academy. Check the complete program here: ✨Here’s the exciting part get 30% off with a festive discount on all of their programs ✨ They can help you with → https://lnkd.in/ghchysUz ✅ Structured curriculum to learn Data tools, Machine Learning, Deep Learning and more. ✅ Personal mentorship from experienced Data professionals. ✅ Live classes, project-based learning, and access to a talented community of people with similar goals of upskilling. Also, get placement support post-completion of the program #DataAnalytics #InterviewQuestions #collab

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Hello Everyone! Here's a scenario-based interview question on Power BI: 𝐒𝐜𝐞𝐧𝐚𝐫𝐢𝐨: You are a data analyst for Nike, tasked with analyzing the sales performance of running shoes across three regions: North America, Europe, and Asia. The company has set a quarterly sales growth target of 15% for each region. They have provided data for the previous quarter’s sales, which includes product categories, revenue, units sold, and regional data. 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 1: Create a new measure in Power BI to calculate the required revenue for each region to meet the 15% growth target. Explain the formula you used for this calculation and how you would structure it within Power BI. 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 2: To track performance, Nike wants to see a comparison of actual sales vs. target sales by month for each region. Describe which type of chart would best represent this monthly variance and justify your answer. Try out these questions and share your answers in the comments

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OMG, Why are there so many buzzwords constantly coming forward in Business & Data Science ? As I am studying more & more about data science & it's applications These buzzwords are keep killing me, ugh 😒 Though online blogs & youtube videos might have provided some context Things are more & more confusing with this forever expanding glossary of Data Science. Is there anyone like me who is facing similar things & Somebody who can answer these questions ? Linkedin please show your Magic

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